What problem do B2B and SaaS companies face in AI search?
The shortlist is moving. Buyers who used to search Google and read ten tabs now ask an AI engine for the best tools for their job. They get a handful of names back, with reasons. If you are not one of them, you may never make the longer list your sales team sees.
The reasons matter as much as the names. An engine might say a rival is "better for small teams" or "easier to set up". Those phrases come from somewhere, usually comparison articles, review sites and Reddit threads. They shape what buyers think before they ever reach your site.
Then there are wrong facts. Old pricing, a plan you retired, a feature you added last year that the engine says you lack. In a considered purchase, one wrong detail can quietly take you out of the running.
What do you get from Axiom GEO?
A clear view of the shortlist, the reasons behind it and the sources that shape it.
- Shortlist tracking. AI visibility tracking runs buyer questions across ChatGPT, Perplexity, Gemini and Claude and records where you appear.
- Why rivals win. Competitor share of voice records every brand named, whether it was recommended and why.
- The sources. AI citation tracking shows the list articles, review sites and pages the engines cite.
- Communities. Reddit insights finds the subreddits AI engines cite in your topic.
- Accuracy. Answer accuracy flags wrong pricing, plans and features, with an offers list that has start and end dates.
- Questions. QA Finder pulls real questions from People Also Ask, Reddit and your own sales call notes.
AI traffic analytics then shows which pages AI engines send visitors to, and AI crawler analytics shows whether bots reach your product and documentation pages.
What about your own site?
Third-party sources matter a lot in B2B, but your own pages still count. Engines need to be sure who you are, what you sell and who it is for. The entity audit checks whether your structured data paints one clear picture of the company, with named authors and verifiable identifiers. Page optimisation scores product and guide pages on structured data, headings, meta, content and freshness, with a fix list for each.
What does a typical month look like?
Most B2B teams settle into a cycle like this.
- Check the shortlist. Look at share of recommendation against your main rivals, per engine.
- Read the reasons. Note the reasons engines give for recommending competitors, and where you are missing.
- Review the sources. Find the comparison posts and threads cited most, and decide which to approach or answer.
- Fix wrong facts. Work through accuracy issues, starting with pricing and plans.
- Fill content gaps. Send AI answer gaps and new questions to Work, and build comparison or use-case pages.
- Report. Share the monthly report with marketing and sales leadership.
Where do sales call notes come in?
Your sales team hears the real questions every day. Paste enquiries or call notes into QA Finder and it pulls out the questions, ignoring personal details. The text is not stored. Those questions often make better prompts than anything from a keyword tool, because they are in the buyer's own words.
Which plan fits a B2B or SaaS company?
Most B2B teams want the engines that cite web pages, since those show which comparison posts and threads matter.
| Plan | Price per month | What it suits |
|---|---|---|
| Professional | £799 | Four engines and answer accuracy, for up to 3 brands |
| Premium | £1,499 | Adds QA Finder and content rewrites for content-led teams |
| Enterprise | Custom | Larger groups with many brands |
Professional is a sound starting point for tracking and accuracy. Premium suits teams that publish guides and comparison pages each month, since QA Finder and content rewrites feed that work directly. The pricing page has the full detail.